DLNM和LSTM神经网络对临沂市手足口病发病的预测效果比较

doi:10.6040/j.issn.1671-7554.0.2021.0707

摘要/Abstract

摘要： 目的运用分布滞后非线性模型(DLNM)和长短期记忆(LSTM)神经网络对山东省临沂市手足口病(HFMD)发病趋势进行分析和预测,为该病的有效防控提供参考依据。方法对临沂市2011年1月1日至2015年12月31日HFMD日发病数据分别进行DLNM和LSTM神经网络建模拟合,以2016年1月1日至2017年12月31日发病数据检验并比较两模型的预测效果。结果 2011年1月1日至2017年12月31日临沂市共报告HFMD 25 999例。DLNM和LSTM神经网络外推预测2016年1月1日至2017年12月31日发病数的均方根误差(RMSE)分别为11.93和5.74,平均绝对误差(MAE)分别为7.93和3.60,提示LSTM神经网络的预测精度优于DLNM,预测结果与实际情况基本一致。结论 LSTM神经网络对临沂市HFMD发病趋势的拟合程度和预测效果较好,可为该病的预测预警提供指导。

关键词: 手足口病, 预测, 分布滞后非线性模型, 长短期记忆神经网络

Abstract: Objective To analyze and predict the incidence trend of hand, foot and mouth disease(HFMD)in Linyi City, Shandang Province by using the distributed lag non-linear model(DLNM)and long-short term memory(LSTM)neural network, and to provide reference for effective prevention and control of the disease. Methods The daily incidence data from Jan. 1, 2011 to Dec. 31, 2015 were collected to establish the DLNM and LSTM neural network, respectively. The daily incidence data from Jan. 1, 2016 to Dec. 31, 2017 were used to test and compare the prediction effects of the two models. Results A total of 25,999 HFMD cases were reported during Jan. 1, 2011 to Dec. 31, 2017. The root mean square error(RMSE)of DLNM and LSTM neural network extrapolation prediction from Jan. 1, 2016 to Dec. 31, 2017 were 11.93 and 5.74, respectively, and the mean absolute deviation(MAE)were 7.93 and 3.60, respectively, indicating the prediction accuracy of LSTM was better than that of DLNM, and the prediction results were basically consistent with the actual situation. Conclusion LSTM neural network has a good fitting and prediction effect on the incidence trend of HFMD in Linyi City, which can provide guidance for the prediction and warning of the disease.

Key words: Hand, foot and mouth disease, Prediction, Distributed lag non-linear model, Long-short term memory neural network

中图分类号:

R181.3

冯一平,孙大鹏,王显军,纪伊曼,刘云霞. DLNM和LSTM神经网络对临沂市手足口病发病的预测效果比较[J]. 山东大学学报 (医学版), 2022, 60(2): 96-101.

FENG Yiping, SUN Dapeng, WANG Xianjun, JI Yiman, LIU Yunxia. Comparison of prediction effects of DLNM and LSTM neural network on the incidence of hand, foot and mouth disease in Linyi City[J]. Journal of Shandong University (Health Sciences), 2022, 60(2): 96-101.

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